Are the disruptors disrupted? Where do Business Analysts fit in?
Interestingly, we have witnessed much of the Fintech boom globally around the middle of last decade (2016) but did it really make much of an impact? Whether it’s ‘Artificial Intelligence’, ‘Machine Learning’ or ‘Internet of Things’ how much have these emerging technologies been able to penetrate banking so far? It`s 2023 and ticking …
These are a few possible questions we are still trying to find answers to...
Before discussing any further on this subject, how many of us know about artificial intelligence being used as early as in the 1940s for the first time by a prodigious English gentleman Sir Alan Turing. Popularly referred to as ‘The father of modern computer science’ introduced a procedure ‘The Turing Test’ which later formed the foundation of cognitive science. For those of us who are not familiar with the name yet I`d recommend to watch the movie ‘The Imitation Game’ just to understand a little bit of the genius of Turing. Sir John Von Neumann was another American genius who made equal contribution by comparing human intelligence to computers.
For those of us who are still new to these concepts I`ll make a fair attempt to briefly explain in a few. Fundamentally, Artificial intelligence (AI) is the branch of computer science that deals with the creation of machines or systems capable of performing functions that would normally require human intelligence. These machines interact with the environment and behave according to the information they receive about it without any human intervention.
The ‘Internet of Things (IOT)’ is a system that connects any electronic device, gadget, machine, microchip, sensor, appliance, or building—just about anything, in fact—to the Internet. E.g. automatically unlocking a door when you need it to open.
Over the last few years banking institutions have made a sincere effort to promote and adapt various emerging technologies. Some of them were really successful at these initiatives but others failed badly, and banks continued falling back to existing systems. One cannot forget the constant buzz around 2017 which made us feel that at some point all existing legacy technologies would be demised and replaced with modern ones of the likes of machine learning (ML) AI, IOT etc. Infact some people started to question if they might end up losing their day jobs by 2020 in this automation storm.
We are in 2023 already and reality seems to be slightly different than what we had thought. ‘Fintech’ industry was able to penetrate in a few areas but as a matter-of-fact complete metamorphosis didn’t really happen. Or did it?
Now the question is, was Fintech really the light bulb moment in Banking?
Knowledge Graphs for example have massive capabilities ranging from creating spectacular visual representations, dashboards, and a mind map of connections but it needs deeper research to apply these capabilities across business units. Many organizations are still researching text mining which gave an initial impression to create true innovation. Amidst these disruptions, I must mention Microsoft Excel has continuously evolved to keep up with the demand in the industry and is able to cater to the needs quite well.
Extraction, Transformation and Load (ETL) tools like XCEPTOR have been able to make a profound impression. Xceptor makes data ingestion, data transformation and process digitization easy. The data automation platform handles any data and document type, in any format, from any channel, to deliver end-to-end automation of complex processes.
On the other hand, Blockchain has been a massive success in trade finance but in other areas of banking it's still a Proof of concept (POC) awaiting approval. One of the primary reasons is that these emerging technologies though have had an array of features to offer and are heavily automated, but innovation teams still struggling justifying the return on those investments. Personally, I do feel at some point we have to take a step back and ask ourselves the right questions, i.e. if we really need to address a problem at hand with these emerging disruptors?
Eliciting the right questions and documenting the Why's has two-fold benefits:
- Money and time are not wasted on unnecessary research & development and unsound assumptions.
- Resources could be redirected to manage other priority issues.
This is exactly why the Business Analysis role becomes critical and it is extremely important to thoroughly understand the capabilities of these solutions and accordingly map them to business problem/problems under question. Often the approach and general tendency is to hunt down less realistic use cases and try to apply some advanced fancy features which probably won't reap many benefits in the long run and will not help automate the existing processes either. Which is why stringent benefit evaluation (i.e. immediate benefits and long-term both) is extremely important before initiating any POCs.
Through this evolving landscape, the role of business analysis is crucial to bring in these new innovations and systems in a more meaningful manner making a smooth road for the disruptors.
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